ArticleProtein science : a publication of the Protein Society1998
Prediction by a neural network of outer membrane beta-strand protein topology.
Article in Protein science : a publication of the Protein Society, 1998. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed.
- A Survey of Current Status in AI-Based Topology Prediction of Transmembrane Proteins.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Protein Sorting Prediction.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Computational prediction of secreted proteins in gram-negative bacteria.Computational and structural biotechnology journal · 2021Review
- A 3-dimensional trimeric β-barrel model for Chlamydia MOMP contains conserved and novel elements of Gram-negative bacterial porins.PloS one · 2013Article
- OMPdb: a database of {beta}-barrel outer membrane proteins from Gram-negative bacteria.Nucleic acids research · 2011Article
- Structure of the voltage dependent anion channel: state of the art.Journal of bioenergetics and biomembranes · 2008Review
- Identification of surface-exposed components of MOMP of Chlamydia trachomatis serovar F.Protein science : a publication of the Protein Society · 2006Article
- Surface expression, single-channel analysis and membrane topology of recombinant Chlamydia trachomatis Major Outer Membrane Protein.BMC microbiology · 2005Article
- Evaluation of methods for predicting the topology of beta-barrel outer membrane proteins and a consensus prediction method.BMC bioinformatics · 2005Article
- A novel outer-membrane anion channel (porin) as part of a putatively two-component transport system for 4-toluenesulphonate in Comamonas testosteroni T-2.The Biochemical journal · 2004Article
- PRED-TMBB: a web server for predicting the topology of beta-barrel outer membrane proteins.Nucleic acids research · 2004Article
- A Hidden Markov Model method, capable of predicting and discriminating beta-barrel outer membrane proteins.BMC bioinformatics · 2004Article
- Structure prediction of membrane proteins.Genomics, proteomics & bioinformatics · 2004Review
- Functional reconstitution, gene isolation and topology modelling of porins from Burkholderia pseudomallei and Burkholderia thailandensis.The Biochemical journal · 2004Article
- The Omp85 family of proteins is essential for outer membrane biogenesis in mitochondria and bacteria.The Journal of cell biology · 2004Article
- Predicting transmembrane beta-barrels in proteomes.Nucleic acids research · 2004Article
- Prediction of the membrane-spanning beta-strands of the major outer membrane protein of Chlamydia.Protein science : a publication of the Protein Society · 2002Article
- The preprotein conducting channel at the inner envelope membrane of plastids.The EMBO journal · 2002Article
- The TOL plasmid pWW0 xylN gene product from Pseudomonas putida is involved in m-xylene uptake.Journal of bacteriology · 2001Article
- Prediction of the transmembrane regions of beta-barrel membrane proteins with a neural network-based predictor.Protein science : a publication of the Protein Society · 2001Article
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5 authors.
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Abstract
An artificial neural network (NN) was trained to predict the topology of bacterial outer membrane (OM) beta-strand proteins. Specifically, the NN predicts the z-coordinate of Calpha atoms in a coordinate frame with the outer membrane in the xy-plane, such that low z-values indicate periplasmic turns, medium z-values indicate transmembrane beta-strands, and high z-values indicate extracellular loops. To obtain a training set, seven OM proteins (porins) with structures known to high resolution were aligned with their pores along the z-axis. The relationship between Calpha z-values and topology was thereby established. To predict the topology of other OM proteins, all seven porins were used for the training set. Z-values (topologies) were predicted for two porins with hitherto unknown structure and for OM proteins not belonging to the porin family, all with insignificant sequence homology to the training set. The results of topology prediction compare favorably with experimental topology data.
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